- Prepare the data
- Basic stripcharts
- Add summary statistics on a stripchart
- Add mean and median points
- Stripchart with box blot and violin plot
- Add mean and standard deviation

- Change point shapes by groups
- Change stripchart colors by groups
- Change the legend position
- Change the order of items in the legend
- Stripchart with multiple groups
- Customized stripcharts
- Infos

This **R tutorial** describes how to create a **stripchart** using **R software** and **ggplot2** package. **Stripcharts** are also known as one dimensional scatter plots. These plots are suitable compared to box plots when sample sizes are small.

The function **geom_jitter()** is used.

*ToothGrowth* data sets are used :

`# Convert the variable dose from a numeric to a factor variableToothGrowth$dose <- as.factor(ToothGrowth$dose)head(ToothGrowth)`

`## len supp dose## 1 4.2 VC 0.5## 2 11.5 VC 0.5## 3 7.3 VC 0.5## 4 5.8 VC 0.5## 5 6.4 VC 0.5## 6 10.0 VC 0.5`

Make sure that the variable *dose* is converted as a factor variable using the above R script.

`library(ggplot2)# Basic stripchartggplot(ToothGrowth, aes(x=dose, y=len)) + geom_jitter()# Change the position# 0.2 : degree of jitter in x directionp<-ggplot(ToothGrowth, aes(x=dose, y=len)) + geom_jitter(position=position_jitter(0.2))p# Rotate the stripchartp + coord_flip()`

Choose which items to display :

`p + scale_x_discrete(limits=c("0.5", "2"))`

**Change point shapes and size** :

`# Change point sizeggplot(ToothGrowth, aes(x=dose, y=len)) + geom_jitter(position=position_jitter(0.2), cex=1.2)# Change shapeggplot(ToothGrowth, aes(x=dose, y=len)) + geom_jitter(position=position_jitter(0.2), shape=17)`

Read more on point shapes : ggplot2 point shapes

The function **stat_summary()** can be used to add mean/median points and more to a stripchart.

## Add mean and median points

`# stripchart with mean pointsp + stat_summary(fun.y=mean, geom="point", shape=18, size=3, color="red")# stripchart with median pointsp + stat_summary(fun.y=median, geom="point", shape=18, size=3, color="red")`

## Stripchart with box blot and violin plot

`# Add basic box plotggplot(ToothGrowth, aes(x=dose, y=len)) + geom_boxplot()+ geom_jitter(position=position_jitter(0.2))# Add notched box plotggplot(ToothGrowth, aes(x=dose, y=len)) + geom_boxplot(notch = TRUE)+ geom_jitter(position=position_jitter(0.2))# Add violin plotggplot(ToothGrowth, aes(x=dose, y=len)) + geom_violin(trim = FALSE)+ geom_jitter(position=position_jitter(0.2))`

Read more on box plot : ggplot2 box plot

Read more on violin plot : ggplot2 violin plot

## Add mean and standard deviation

The function **mean_sdl** is used. *mean_sdl* computes the *mean* plus or minus a *constant* times the *standard deviation*.

In the R code below, the constant is specified using the argument *mult* (mult = 1). By default mult = 2.

The mean +/- SD can be added as a *crossbar* or a *pointrange* :

`p <- ggplot(ToothGrowth, aes(x=dose, y=len)) + geom_jitter(position=position_jitter(0.2))p + stat_summary(fun.data="mean_sdl", mult=1, geom="crossbar", width=0.5)p + stat_summary(fun.data=mean_sdl, mult=1, geom="pointrange", color="red")`

Note that, you can also define a custom function to produce summary statistics as follow

`# Function to produce summary statistics (mean and +/- sd)data_summary <- function(x) { m <- mean(x) ymin <- m-sd(x) ymax <- m+sd(x) return(c(y=m,ymin=ymin,ymax=ymax))}`

Use a custom summary function :

`p + stat_summary(fun.data=data_summary, color="blue")`

In the R code below, point shapes are controlled automatically by the variable *dose*.

You can also set point shapes manually using the function **scale_shape_manual()**

`# Change point shapes by groupsp<-ggplot(ToothGrowth, aes(x=dose, y=len, shape=dose)) + geom_jitter(position=position_jitter(0.2))p# Change point shapes manuallyp + scale_shape_manual(values=c(1,17,19))`

Read more on point shapes : ggplot2 point shapes

In the R code below, point colors of the stripchart are automatically controlled by the levels of *dose* :

`# Use single colorggplot(ToothGrowth, aes(x=dose, y=len)) + geom_jitter(position=position_jitter(0.2), color="red")# Change stripchart colors by groupsp<-ggplot(ToothGrowth, aes(x=dose, y=len, color=dose)) + geom_jitter(position=position_jitter(0.2))p`

It is also possible to *change manually stripchart colors* using the functions :

*scale_color_manual()*: to use custom colors*scale_color_brewer()*: to use color palettes from*RColorBrewer*package*scale_color_grey()*: to use grey color palettes

`# Use custom color palettesp+scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))# Use brewer color palettesp+scale_color_brewer(palette="Dark2")# Use grey scalep + scale_color_grey() + theme_classic()`

Read more on ggplot2 colors here : ggplot2 colors

`p + theme(legend.position="top")p + theme(legend.position="bottom")p + theme(legend.position="none")# Remove legend`

The allowed values for the arguments **legend.position** are : “left”,“top”, “right”, “bottom”.

Read more on ggplot legends : ggplot2 legend

The function **scale_x_discrete** can be used to change the order of items to “2”, “0.5”, “1” :

`p + scale_x_discrete(limits=c("2", "0.5", "1"))`

`# Change stripchart colors by groupsggplot(ToothGrowth, aes(x=dose, y=len, color=supp)) + geom_jitter(position=position_jitter(0.2))# Change the position : interval between stripchart of the same groupp<-ggplot(ToothGrowth, aes(x=dose, y=len, color=supp, shape=supp)) + geom_jitter(position=position_dodge(0.8))p`

Change stripchart colors and add box plots :

`# Change colorsp+scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))# Add box plotsggplot(ToothGrowth, aes(x=dose, y=len, color=supp)) + geom_boxplot(color="black")+ geom_jitter(position=position_jitter(0.2))# Change the positionggplot(ToothGrowth, aes(x=dose, y=len, color=supp)) + geom_boxplot(position=position_dodge(0.8))+ geom_jitter(position=position_dodge(0.8))`

`# Basic stripchartggplot(ToothGrowth, aes(x=dose, y=len)) + geom_boxplot()+ geom_jitter(position=position_jitter(0.2))+ labs(title="Plot of length by dose",x="Dose (mg)", y = "Length")+ theme_classic()# Change color/shape by groupsp <- ggplot(ToothGrowth, aes(x=dose, y=len, color=dose, shape=dose)) + geom_jitter(position=position_jitter(0.2))+ labs(title="Plot of length by dose",x="Dose (mg)", y = "Length")p + theme_classic()`

Change colors manually :

`# Continuous colorsp + scale_color_brewer(palette="Blues") + theme_classic()# Discrete colorsp + scale_color_brewer(palette="Dark2") + theme_minimal()# Gradient colorsp + scale_color_brewer(palette="RdBu")`

Read more on ggplot2 colors here : ggplot2 colors

This analysis has been performed using **R software** (ver. 3.1.2) and **ggplot2** (ver. 1.0.0)